3D Hand Gesture Navigation via Range Finding Imaging
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Solution Overview
Problem
Conventional 2D imaging techniques struggle with reliable and efficient detection of 3D hand gestures in varying environments, particularly in situations with changing illumination, and fail to accurately distinguish intentional from non-intentional hand movements, making them unsuitable for robust human-to-computer interactions in GUIs.
Innovation Solution
A method using 3D range finding imaging systems to detect and track specific points of interest on a user's hand, recognizing natural gestures by determining when two points move close together, maintaining interaction during a defined hand pose, and releasing interaction when the pose is released, allowing for precise control of GUI interactions like scrolling, zooming, and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional 2D imaging techniques are used for gesture detection, then device complexity is reduced, but measurement precision and reliability of 3D hand gesture detection deteriorate
Solution Approach 1:
The patent transitions from 2D imaging to 3D range finding imaging systems. The system captures depth information in addition to color information, enabling accurate 3D hand gesture detection. This dimensional change resolves the contradiction by providing the necessary depth data for precise 3D measurement while maintaining reasonable system complexity through integrated sensors.
Solution Approach 2:
The patent changes the imaging parameters by using range finding capabilities to measure distance and depth. Instead of relying solely on 2D color image analysis, the system incorporates depth maps and distance measurements as additional parameters for gesture recognition, significantly improving measurement precision.
2Ease of operation
If 2D color camera with background learning is used, then ease of operation is improved, but reliability of gesture detection in varying illumination deteriorates
Solution Approach 1:
The patent adds the depth dimension to gesture detection, using range finding imaging to capture 3D hand positions and gestures. This depth information provides a new dimension for distinguishing intentional gestures from background variations, improving reliability in varying illumination conditions while maintaining ease of operation through natural hand movements.
Solution Approach 2:
The patent introduces depth information as an intermediary that mediates between the 2D color camera and gesture recognition. The depth map serves as an additional layer of information that helps distinguish foreground hand gestures from background variations, improving detection reliability without complicating the user interaction.
3Device complexity
If conventional 2D imaging is used for hand detection, then device complexity is reduced, but ability to distinguish intentional from non-intentional gestures deteriorates
Solution Approach 1:
The patent uses 3D range finding imaging to capture depth information that reveals hand posture and gesture configuration. This additional dimensional data enables the system to distinguish intentional gestures (with specific 3D configurations) from non-intentional movements, preventing loss of gesture intentionality information.
Solution Approach 2:
The patent replaces 2D color-based hand detection with 3D range finding imaging. This substitution provides direct depth measurement capability, enabling the system to analyze hand gesture configurations in three dimensions and accurately determine gesture intentionality based on spatial relationships between hand components.
4Measurement precision
If 3D range finding imaging is used for gesture recognition, then measurement precision and reliability are improved, but device complexity increases
Solution Approach 1:
The patent merges color imaging and range finding imaging into a single integrated system. By combining these two imaging modalities, the system achieves high measurement precision for 3D gesture detection while avoiding the complexity of separate independent systems. The integrated approach shares processing resources and coordinate systems.
Solution Approach 2:
The imaging system is designed with multi-functionality, serving both color-based gesture recognition and depth-based 3D measurement. This universal system handles multiple tasks (gesture detection, depth mapping, background segmentation) through a single integrated platform, reducing overall device complexity compared to specialized separate systems.
Data Source
AI summary
Described herein is a method for enabling human-to-computer three-dimensional hand gesture-based natural interactions. From depth images provided by a range finding imaging system, the method enables efficient and robust detection of a particular sequence of natural gestures including a beginning (start), and an ending (stop) of a predetermined type of natural gestures for delimiting the period during which a control (interaction) gesture is operating in an environment wherein a user is freely moving his hands. The invention is more particularly, although not exclusively, concerned by detection without any false positives nor delay, of intentionally performed natural gesture subsequent to a starting finger tip or hand tip based natural gesture so as to provide efficient and robust navigation, zooming and scrolling interactions within a graphical user interface up until the ending finger tip or hand tip based natural gesture is detected.